System and method for using a satellite positioning system to filter wlan access points in a hybrid positioning system

ABSTRACT

This disclosure describes a system and method for using a satellite positioning system to filter WLAN access points in a hybrid positioning system. In some embodiments, the method can include detecting WLAN APs in range of the WLAN and satellite enabled device, obtaining satellite measurements from at least two satellites to provide a plurality of possible satellite locations of the device, and providing a weight for each AP based on the distance from the WLAN APs to the possible satellite locations of the device.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.12/479,734, entitled System And Method For Using A Satellite PositioningSystem To Filter WLAN Access Points In A Hybrid Positioning System,filed Jun. 5, 2009, now U.S. Pat. No. 7,999,742, which claims thebenefit under 35 U.S.C. §119(e) of U.S. Provisional Application No.61/059,580, filed on Jun. 6, 2008, entitled Integrated WLAN-based andSatellite-based Positioning System, both incorporated by referenceherein in their entirety.

This application is related to the following references:

U.S. patent application Ser. No. 12/479,718, filed Jun. 5, 2009 andentitled “Method and System for Determining Location Using a HybridSatellite and WLAN Positioning System by Selecting the Best WLAN-PSSolution;”

U.S. patent application Ser. No. 12/479,721, filed Jun. 5, 2009 andentitled “Systems and methods for Using Environmental Information in aHybrid Positioning System;”

U.S. patent application Ser. No. 12/479,722, filed Jun. 5, 2009 andentitled “Systems and Methods for Maintaining Clock Bias Accuracy in aHybrid Positioning System;”

U.S. patent application Ser. No. 12/479,723, filed Jun. 5, 2009 andentitled “System and Method for Refining a WLAN-PS Estimated LocationUsing Satellite Measurements in a Hybrid Positioning System;”

U.S. patent application Ser. No. 12/479,724, filed Jun. 5, 2009 andentitled “Systems and Methods for Determining Position Using a WLAN-PSEstimated Position as an Initial Position in a Hybrid PositioningSystem;”

U.S. patent application Ser. No. 12/479,727, filed Jun. 5, 2009 andentitled “Methods and Systems for Improving the Accuracy of ExpectedError Estimation in a Hybrid Positioning System;” and

U.S. patent application Ser. No. 12/479,729, filed Jun. 5, 2009 andentitled “Methods and Systems for Stationary User Detection in a HybridPositioning System.”

BACKGROUND

1. Field

The disclosure generally relates to hybrid positioning systems and, morespecifically, to methods of integrating wireless local area network(WLAN)-based positioning system (WLAN-PS) and satellite-basedpositioning system (SPS) to improve accuracy of location estimates,increase availability of the positioning service to more users, reducepower consumption, and also to improve estimation of the expected errorin a user's position estimate.

2. Description of Related Art

In recent years the number of mobile computing devices has increaseddramatically, creating the need for more advanced mobile and wirelessservices. Mobile email, walkie-talkie services, multi-player gaming, andcall-following are examples of how new applications are emerging formobile devices. In addition, users are beginning to demand/seekapplications that not only utilize their current location but also sharethat location information with others. Parents wish to keep track oftheir children, supervisors need to track the locations of the company'sdelivery vehicles, and a business traveler looks to find the nearestpharmacy to pick up a prescription. All of these examples require anindividual to know his own current location or the location of someoneelse. To date, we all rely on asking for directions, calling someone toask their whereabouts or having workers check-in from time to time toreport their positions.

Location-based services are an emerging area of mobile applications thatleverage the ability of new devices to calculate their currentgeographic positions and report them to a user or to a service. Examplesof these services range from obtaining local weather, traffic updates,and driving directions to child trackers, buddy finders, and urbanconcierge services. These new location-sensitive devices rely on avariety of technologies that all use the same general concept. Bymeasuring radio signals originating from known reference points, thesedevices can mathematically calculate the user's position relative tothese reference points. Each of these approaches has its strengths andweaknesses, depending upon the nature of the signals and measurements,and the positioning algorithms employed.

The Navstar Global Positioning System (GPS) operated by the USGovernment leverages about two-dozen orbiting satellites in medium-earthorbits as reference points. A user equipped with a GPS receiver canestimate his three-dimensional position (latitude, longitude, andaltitude) anywhere at any time within several meters of the truelocation, as long as the receiver can see enough of the sky to have fouror more satellites “in view.” Cellular carriers have used signalsoriginating from and received at cell towers to determine a user's or amobile device's location. Assisted GPS (AGPS) is another model thatcombines both GPS and cellular tower techniques to estimate thelocations of mobile users who may be indoors and must cope withattenuation of GPS signals on account of sky blockage. In this model,the cellular network attempts to help a GPS receiver improve its signalreception by transmitting information about the satellite positions,their clock offsets, a precise estimate of the current time, and a roughlocation of the user based on the location of cell towers. Nodistinction is made in what follows between GPS and AGPS.

All positioning systems using satellites as reference points arereferred to herein as Satellite-based Positioning System (SPS). WhileGPS is the only operational SPS at this writing, other systems are underdevelopment or in planning. A Russian system called GLONASS and aEuropean system called Galileo may become operational in the next fewyears. All such systems are referred to herein as SPS. GPS, GLONASS andGalileo are all based on the same basic idea of trilateration, i.e.,estimating a position on the basis of measurements of ranges to thesatellites whose positions are known. In each case, the satellitestransmit the values of certain parameters which allow the receiver tocompute the satellite position at a specific instant. The ranges tosatellites from a receiver are measured in terms of the transit times ofthe signals. These range measurements can contain a common bias due tothe lack of synchronization between the satellite and receiver (userdevice) clocks, and are referred to as pseudoranges. The lack ofsynchronization between the satellite clock and the receiver (userdevice) clock results in a difference between the receiver clock and thesatellite clock, which is referred to as internal SPS receiver clockbias or receiver clock bias, here. In order to estimate a threedimensional position there is a need for four satellites to estimatereceiver clock bias along with three dimensional measurements.Additional measurements from each satellite correspond to pseudorangerates in the form of Doppler frequency. References below to raw SPSmeasurements are intended generally to mean pseudoranges and Dopplerfrequency measurements. References to SPS data are intended generally tomean data broadcast by the satellites. References to an SPS equation areintended to mean a mathematical equation relating the measurements anddata from a satellite to the position and velocity of an SPS receiver.

WLAN-based positioning is a technology which uses WLAN access points todetermine the location of mobile users. Metro-wide WLAN-basedpositioning systems have been explored by a several research labs. Themost important research efforts in this area have been conducted by thePlaceLab (www.placelab.com, a project sponsored by Microsoft and Intel);the University of California, San Diego ActiveCampus project(ActiveCampus—Sustaining Educational Communities through MobileTechnology, technical report #CS2002-0714); and the MIT campus-widelocation system. There is only one commercial metropolitan WLAN-basedpositioning system in the market at the time of this writing, and it isreferred to herein as the WPS (WiFi positioning system) product ofSkyhook Wireless, Inc. (www.skyhookwireless.com).

FIG. 1 depicts a conventional WLAN-based positioning system based onWiFi signals. The positioning system includes positioning software 103that resides on a mobile or user device 101. Throughout a particulartarget geographical area, there are a plurality of fixed wireless accesspoints 102 that transmit information using control/common channelsignals. The device 101 monitors these transmissions. Each access pointcontains a unique hardware identifier known as a MAC address. The clientpositioning software 103 receives transmissions from the 802.11 accesspoints in its range and calculates the geographic location of thecomputing device using the characteristics of the radio signals. Thosecharacteristics include the MAC addresses, the unique identifiers of the802.11 access points, the Time of Arrival (TOA) of the signals, and thesignal strength at the client device 101. The client software 103compares the observed 802.11 access points with those in its referencedatabase 104 of access points. This reference database 104 may or maynot reside in the device 101. The reference database 104 contains thecalculated geographic locations and power profiles of all access pointsthe system has collected. A power profile may be generated from acollection of measurements of the signal power or signal TOA at variouslocations. Using these known locations or power profiles, the clientsoftware 103 calculates the position of the user device 101 relative tothe known positions of the access points 102 and determines the device's101 absolute geographic coordinates in the form of latitude andlongitude or latitude, longitude, and altitude. These readings then canbe fed to location-based applications such as friend finders, localsearch web sites, fleet management systems, and an E911 service.

In the discussion herein, raw WLAN measurements from an access point aregenerally intended to mean received signal strength (RSS) and/or timesof arrival (TOAs) and/or time differences of arrival (TDOAs). Referencesto data are generally intended to mean the MAC address, one or morerecord(s) of it, one or more power profile(s), and other attributesbased on previous measurements of that access point. References to aWLAN-PS equation are intended to mean a mathematical equation relatingthe WLAN-PS measurements and data to the location of the mobile device.

A WLAN-based positioning systems can be used indoor or outdoor. The onlyrequirement is presence of WLAN access points in the vicinity of theuser. The WLAN-based position systems can be leveraged using existingoff-the-shelf WLAN cards without any modification other than to employlogic to estimate position.

FIG. 2 illustrates a conventional way of integrating WLAN-PS and SPS,which consists of a WLAN-PS 201 and a SPS 206, and a location combininglogic 210.

WLAN-PS 201 and SPS 206 are stand-alone systems and each can operateindependently of the other system. Thus the result of each system can becalculated independent of the other system. The estimated location alongwith the expected error estimation of each system can be fed to thelocation combining logic 210. The expected error estimation is alsoreferred to as HPE (horizontal positioning error) herein. The nominalrate of location update of SPS 206 and WLAN-PS 201 is once a second. Thelocation combining logic 210 combines location estimates calculated inthe same second by both systems.

WLAN-PS 201 is a conventional system which estimates the location of amobile device by using WLAN access points. WLAN-PS 201 can include ascanner of WLAN APs 202, a device to select WLAN APs 203, atrilateration module 204, and HPE estimation device 205.

WLAN Scanner 202 detects WLAN APs surrounding the mobile device bydetecting the received power (RSS, received signal strength) and/or timeof arrival (TOA) of the signal. Different methods can be used to detectWLAN APs including active scanning, passive scanning, or combination ofpassive and active scanning.

The select WLAN APs device 203 selects the best set of WLAN APs toestimate location of the mobile device. For example, if ten WLAN APs aredetected and one AP is located in Chicago and the others are located inBoston, without any other information, the Boston APs are selected. Thisis an indication that Chicago AP has been moved to Boston. In theconventional system the best set of WLAN APs is selected based ongeographical distribution of WLAN APs in addition to correspondingparameters of WLAN APs, including received signal strength, signal tonoise ration, and the probability of being moved.

Trilateration module 204 uses WLAN APs and corresponding measurementsand characteristics to estimate location of the mobile device. Receivedsignal strength or TOA measurements from WLAN AP are used to estimatedistance of the mobile device to the WLAN AP. The aggregation ofdistance estimates from different WLAN APs with known location is usedto calculate location of the mobile device. Trilateration 204 also canuse a method which is called nearest neighbor, in which a location witha power profile similar or closest to the power reading of the mobiledevice is reported as the final location of the mobile device. The powerprofile of each WLAN AP or entire coverage area can be found in thecalibration phase of the system by detailed survey of the coverage area.

HPE estimation device 205 is the module which estimates the expectederror of the position estimate of the mobile device. The HPE, orHorizontal Positioning Error is calculated based on previously scannedAPs and their characteristics and also characteristics of the receivedsignal, as it was explained in co-pending Skyhook Wireless applicationSer. No. 11/625,450 entitled “System and Method for EstimatingPositioning Error Within a WLAN Based Positioning System,” the entiredisclosure of which is hereby incorporated by reference.

SPS system 206 consists of a satellite signal receiver and measurementdevice 207, trilateration device 208, and the SPS HPE estimation module209.

The satellite signal receiver and measurement device 207 receivessignals from the satellites in view of the device, decodes the receivedsignal, and measures the satellite parameters from each satellite. Themeasurements can include pseudorange, carrier frequency, and Dopplerfrequency.

The trilateration device 208 uses measurements from at least foursatellites and location of the satellites in view to estimate locationof the user device, velocity, and direction of travel of the mobiledevice.

HPE estimation device 209 estimates the expected error of the estimatedlocation. The HPE estimation device 209 is conventional and calculatesexpected error based on geometry of the satellites and signal quality ofthe received signal from satellites, for example, DOP (dilution ofprecision), and C/N (carrier to noise ratio).

Location combining logic 210 receives location and HPE estimatescalculated for almost the same second from WLAN-PS 201 and SPS 206. Inother words, measurements and estimations which are made at the sametime are compared and combined. Practically, measurements andestimations within one second can be considered the same time. Thelocation combining logic 210 of the user device reports one estimatedlocation by selecting one of them or linearly combining them. Forexample, location combining logic might select one of the estimatedlocations provided by WLAN-PS 201 or SPS 206 based on reported expectederror or HPE, or it might report weighted average of estimated locationsby both systems according to the HPE.

SUMMARY

This disclosure describes a system and method for using a satellitepositioning system to filter WLAN access points in a hybrid positioningsystem. In some embodiments, the method can include detecting WLAN APsin range of the WLAN and satellite enabled device, obtaining satellitemeasurements from at least two satellites to provide a plurality ofpossible satellite locations of the device, and providing a weight foreach AP based on the distance from the WLAN APs to the possiblesatellite locations of the device.

In some embodiments, the method can include using the weight for each APin a location algorithm to determine the location of the device.

In some embodiments, the possible satellite locations of the device caninclude a region of possible location solutions for the device.

In some embodiments a high weight can correspond to an AP that is closeto the possible satellite locations of the device.

In some embodiments, close to the satellite estimate of the location ofthe device can include a distance within one order of magnitude of thecoverage area of the AP.

In some embodiments, a low weight can correspond to an AP that is farfrom the satellite estimation of the location of the device.

In some embodiments, a WLAN AP can be far from the location of thedevice if the AP is located at a distance an order of magnitude abovethe coverage area of the AP.

In some embodiments, if the WLAN AP is determined to be far from thepossible satellite locations of the device, the position of the WLAN andsatellite enabled device can be calculated without data from the farWLAN AP.

In some embodiments, the weight can be based on the consistency betweenthe location of the WLAN APs and the possible satellite locations of thedevice.

In some embodiments, the method can include eliminating WLAN APs whichare not consistent with the possible satellite locations of the device.

In some embodiments, the WLAN AP location consistency with the satelliteinformation can be measured by applying each of the WLAN AP locations tothe satellite measurements and calculating the internal SPS receiverclock bias for each WLAN AP location.

In some embodiments, the method can include calculating an internal SPSreceiver clock bias by considering the location of each WLAN AP as aninitial position and the measurements from each satellite.

In some embodiments, the consistency of the internal SPS receiver clockbias for each of the WLAN AP locations can be used as an indication ofdistance between the WLAN AP location and the possible satellite devicelocations.

In some embodiments, the method can include calculating the consistencyof the internal SPS receiver clock bias for each WLAN AP location caninclude calculating the standard deviation or the mean square error ofthe internal SPS receiver clock bias.

In some embodiments, the application describes a system for determiningthe location of a WLAN and satellite enabled device by using satellitemeasurements to weigh WLAN access points (APs), the system can include ahybrid positioning module which can include a WLAN module for receivinginformation from one or more WLAN access points, a satellite positioningmodule for providing a plurality of possible device locations of thedevice based on satellite information from at least two differentsatellites, and logic contained in the positioning module for providinga weight for each AP based on the distance from the WLAN APs to thepossible satellite device locations of the device.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

For a more complete understanding of various embodiments of the presentinvention, reference is now made to the following descriptions taken inconnection with the accompanying drawings in which:

FIG. 1 illustrates a high-level architecture of a WLAN positing system;

FIG. 2 illustrates a system for a conventional way of integratingWLAN-PS and SPS;

FIG. 3 illustrates a system for providing a WLAN-PS and SPS integratedsolution according to some embodiments of the disclosed subject matter;

FIG. 4 illustrates an example of selecting a solution between possibleWLAN-PS solutions using raw SPS measurements from two satellitesaccording to some embodiments of the disclosed subject matter;

FIG. 5 illustrates a system for integrating WLAN-PS and SPS in which rawSPS measurements are provided to WLAN-PS to select the best solutionaccording to some embodiments of the disclosed subject matter;

FIG. 6 illustrates an example of selecting a solution between possibleWLAN-PS solutions based on SPS possible solutions according to someembodiments of the disclosed subject matter;

FIG. 7 illustrates an example of selecting the best set of WLAN APsbased on raw SPS measurements according to some embodiments of thedisclosed subject matter;

FIG. 8 illustrates a system for integrating WLAN-PS and SPS and usingraw SPS measurements from two or more satellites to select a set of WLANAPs in WLAN-PS according to some embodiments of the disclosed subjectmatter;

FIG. 9 illustrates a system for examining the location estimate anduncertainty provided by WLAN-PS against SPS in order to find the bestestimate of the location of a mobile device according to someembodiments of the disclosed subject matter;

FIG. 10 illustrates a system for examining the location estimate anduncertainty provided by WLAN-PS against SPS in order to find the bestestimate of the location of a mobile device by using the grid methodaccording to some embodiments of the disclosed subject matter;

FIG. 11 illustrates a system for integrating WLAN-PS and SPS, in whichraw SPS measurements are used to refine WLAN-PS location estimateaccording to some embodiments of the disclosed subject matter;

FIG. 12 illustrates a system for integrating WLAN-PS and SPS, in whichas WLAN-PS location estimate is provided as initial location estimateaccording to some embodiments of the disclosed subject matter;

FIG. 13 illustrates an example for increasing accuracy of the estimationof expected error by using SPS and WLAN-PS information according to someembodiments of the disclosed subject matter;

FIG. 14 illustrates a system for increasing accuracy of the estimationof expected error by using SPS and WLAN-PS information according to someembodiments of the disclosed subject matter;

FIG. 15 illustrates a system for stationary user detection based on twoor more satellites according to some embodiments of the disclosedsubject matter.

DETAILED DESCRIPTION

Embodiments of the disclosed subject matter provide a method ofintegrating a WLAN-based positioning system (WLAN-PS) and asatellite-based positioning system (SPS) to create a hybrid positioningsystem. An integrated or hybrid system refers to a system which combinesthe measurements from one or more systems to improve the accuracy of thepositioning and velocity and bearing estimates and the accuracy ofexpected error estimate, and to reduce consumed power as compared toeach individual system working independently. The method of integratinga WLAN-PS and SPS to create a hybrid positioning system can add raw SPSmeasurements as another input to WLAN-PS and WLAN-PS final estimationsas another input to SPS. Raw SPS measurements from two or moresatellites can assist the WLAN-PS to increase the accuracy of positionestimate, HPE, and stationary user detection. WLAN-PS initial positionestimate and other estimations also can help SPS to reduce time to firstfix (TTFF) and power consumption. A hybrid positioning system also canreduce power consumption compared to WLAN-PS and SPS workingindependently by deactivating WLAN-PS or SPS when they are not addingvalue in terms of increasing accuracy or other estimations.

FIG. 3 illustrates a block diagram of the hybrid system of a WLAN-PS 301and a SPS 306.

SPS 306 is an off-the-shelf, conventional satellite positioning devicewhich consists of the same devices as SPS 206 in FIG. 2, with additionof an output 311 and an input 312 from the WLAN-PS (discussed in moredetail herein). Satellite receiver and measurement device 207 is part ofevery conventional SPS receiver 306, and raw SPS measurements are anessential part of the SPS measurement. However, here the raw SPSmeasurements are used outside the SPS 306, as is shown by output 311.Not all the commercial SPS receivers expose the raw SPS measurements todevices outside SPS 306. For example, Star III GPS manufactured by SiRFTechnology, Inc. (San Jose, Calif.) provides raw SPS measurements aspart of its standard interface. However there are some other GPSreceivers that do not provide such measurements. For the SPS receiversthat do not expose raw SPS measurements as part of their standardinterface, the SPS receiver 306 is modified to permit access to the rawSPS measurements.

The WLAN-PS 301 functions in a similar manner as the WLAN-PS 201 shownin FIG. 2 except that it is configured to receive raw SPS measurements311. The integration of the raw SPS measurement with WLAN-PS 301 changesthe design of WLAN APs selection device 303, trilateration device 304,and HPE estimation device 305. The WLAN-PS 301 can take advantage of theraw SPS measurements when at least two satellites are acquired, evenwithout any fix or solution from the SPS 306.

This design change of WLAN-PS 301 after receiving raw SPS measurementsis discussed in more detail herein.

Under one embodiment, the disclosed method integrates a WLAN-basedpositioning system (WLAN-PS) and a satellite-based positioning system(SPS) in which the WLAN-PS provides a set of possible locations of amobile device, and among the possible locations, the one which fits theSPS measurements the best is selected as the final position estimate.

This embodiment also can provide a method to integrate WLAN-basedpositioning system (WLAN-PS) and satellite-based positioning system(SPS) in which the WLAN-PS provides a set of possible locations for themobile device, and the possible locations are weighted according totheir distance to a plurality of possible SPS device location solutions.In other words, weights are assigned to WLAN-PS possible solutionsaccording how well they correspond to the satellite measurements. Afterassigning a weight to each possible location, various algorithms can beused to combine or select WLAN-PS possible locations. For example, thefinal reported location can be weighted by an average of all possiblelocations, low weight locations can be removed from the weightedaverage, or only the highest weighted location can be reported.Selection can be a special case of weighting, in which the respectiveweights are zero and one.

For example, because of the high density of WLAN APs in some areas,WLAN-PS can detect tens of WLAN APs in a given location. The detectedWLAN APs may form more than one cluster. A cluster is defined as a setof APs in the coverage area of each other. If the coverage of a WLAN APis not known, a nominal coverage can be considered. Nominal coverage ortypical coverage of a WLAN AP is found statistically by measuringcoverage for thousands of WLAN APs, and it is reported numbers between100 m and 250 m at the time of writing this document. For example, if amobile device detects fifteen WLAN APs, in which ten of them are locatedin a high-rise building and the other five are located in an officebuilding far from the high-rise building (for example, 500 meters awayfrom the high rise building), the detected WLAN APs can be considered astwo clusters with a size of ten and five, respectively. Conventionalpositioning algorithms would select the cluster with a higher number ofAPs: the cluster of ten APs. Under the conventional approach, thelocation would be somewhere in the high-rise building. However, if rawSPS measurements from two or more satellites are considered with thecluster information, even with no location estimate from SPS, the rawSPS measurements can be used to select the appropriate cluster of WLANAPs from the plurality of clusters. In this example, the cluster of fiveWLAN APs might be selected as the closest cluster to the location of themobile device, because it also satisfies the SPS equations. SPSmeasurements also can be used to assign a weight to the clusters of fiveand ten APs according to their estimated distance from possible SPSsolutions. After assigning a weight to clusters, logic can be used tocombine the estimation results of clusters and report only one location.For example, the weighted average of estimation results of clusters,estimations of the cluster with maximum weight, or average of estimationof clusters with higher weights can be reported as final estimationresults.

The first step is detecting WLAN access points, which will be used asreference points to locate the user device. WLAN access points arerandomly distributed, and they also might move over time. Therefore, theWLAN positioning system applies a clustering algorithm to identify allthe clusters of WLAN access points that are detected by the end user.

A cluster of WLAN access points is a set of WLAN access points which arein the coverage area of each other. WLAN access points which are fartherthan a normal coverage of an access point from the cluster areconsidered as a new cluster.

For example, a user detects four access points and three of them arelocated in Boston and one of them in Seattle. Therefore, they form twoclusters: one in Boston with three WLAN access points and one in Seattlewith one WLAN access point. Each cluster of WLAN access point can resultto a separate location in a WLAN positioning system. If the mobiledevice also acquires signals from two or more satellites, the satellitemeasurements can be used to select the cluster of WLAN access points orreject clusters of WLAN access points. Two or more satellitemeasurements provide a set of solutions in a form of a region (volume,surface or a curve). The proximity of possible WPS solutions to SPSpossible solutions can be criteria to weight, select, or reject WPSsolutions. In other words, the closer the WLAN-PS solution to the SPSsolutions, the higher the quality of the WLAN-PS solution.

For example, FIG. 4 shows a WLAN-PS 401, which consists of five WLANaccess points 404. The WLAN access points form two clusters in thisexample, a first cluster 402 and a second cluster 403. Each cluster canbe used to estimate the location of the user device. If the user deviceacquires a signal from at least two satellites 405, the possiblesolutions of the two or more satellites 406 can be used to select oreliminate some clusters. In this example, possible solution of the twoor more satellites is shown as a band 406. Cluster 402 is closer to thepossible satellite solutions band 406 than cluster 403. Therefore,cluster 402 can be selected and cluster 403 can be rejected.

FIG. 5 illustrates block diagram of integrated solution of SPS andWLAN-PS. SPS 506 can be a standard, off-the-shelf device, but it has tobe able to provide raw SPS measurements as discussed in FIG. 3. The rawSPS measurements 311 are directed to WLAN APs 503 and trilaterationdevice 504.

The WLAN APs selection devices 503 receives the data from WLAN scanner202 as an input. The WLAN APs selection device 503 clusters WLAN APsbased on the distance between the access points. The WLAN APs selectiondevice 503 not only identifies clusters, but also selects a differentset of WLAN APs for each cluster. Each different cluster may result in adifferent location estimate. All of the different sets of clusters canbe used in the trilateration device 504 and may result in a differentlocation estimate. The location estimates based on clusters can beweighted according to the cluster distance from the SPS possiblesolutions or can be selected according to their cluster distance fromSPS possible solutions. A cluster can be assigned a high weight if it isconsidered close (at a small distance) from the satellite distancesolution. For example, if the cluster is located on the order of 10meters away from the satellite distance solution. A cluster can beassigned a low weight if it is considered far (at a large distance) fromthe satellite distance solution, for example, if it is located on theorder of 100 or 1,000 meters away from the satellite distance solution.

The SPS solutions can be found as follows. In each satellitemeasurement, there are generally four unknowns coordinates of locationof the mobile device, (x,y,z) and internal clock bias of SPS receiver.The raw SPS measurements from two or more satellites can be used toeliminate the internal clock bias of the SPS receiver from theequations. In this case, the result is going to be a function ofcoordinates of the location of the user device, (x,y,z), which can bewritten as a general form as follows:

F(x,y,z)=0.

This function can represent an area, a surface, or a curve based onnumber of satellites. Therefore, raw SPS measurements from two or moresatellites can result in a set of possible solutions, even withouthaving a final location estimate.

The distance between the different solutions of WLAN-PS and possiblesolutions of SPS can be used as criteria to weigh each WLAN-PS solution.After assigning a weight to each WLAN-PS possible solution, logic can beused to combine the solution or select the solution from the possiblesolutions.

Further, the consistency between the SPS measurements and the locationsprovided by the WLAN-PS can be used as an indication of distance betweenthe locations provided by the WLAN-PS and location of the mobile device.The location of the user device can be calculated by (1) using thepossible WLAN-PS locations as rough estimates of the location of theuser device (i.e., using each possible WLAN-PS location as the x,y,z)and (2) calculating the final unknown, internal satellite receiver clockbias, for each WLAN-PS location estimate using the measurements fromeach satellite. The consistency between the calculated internalsatellite receiver clock biases (calculated for each satellite in view)for each WLAN location estimate can be used as an indicator of distancebetween WLAN-PS's location estimate and the mobile device actuallocation. Good WLAN-PS estimates will have consistent receiver clockbias estimates, i.e., when that WLAN-PS estimated location is used asthe x,y,z location, for each satellite, the receiver clock bias will besubstantially the same, for example, within about 10% of each other.However, if the WLAN-PS location is a poor estimate of the location ofthe user device, the WLAN-PS location will produce varied satellitereceiver clock bias estimates for each satellite, for example, thereceiver clock biases will vary by at more than 10%.

If clock bias which is found for each satellite measurement is denotedby Ci, the consistency of Ci can be used as a measure of distancebetween a given position (in this case, locations determined by theWLAN-PS) and the locations that satisfy the satellite equations. Theconsistency of Ci can be measured with different mathematicalapproaches, like standard deviation of Ci, or mean square error of Ciestimation as follows:

$\overset{\_}{C} = \frac{\sum\limits_{i = 1}^{N}C_{i}}{N}$${M\; S\; E} = \frac{\sum\limits_{i = 1}^{N}\left( {C_{i} - \overset{\_}{C}} \right)^{2}}{N}$

The value of MSE can be used as an indicator of the consistency of theCi samples. Therefore, all possible locations of WLAN-PS can be examinedwith SPS raw measurements, and the consistency of Ci can be used as anindicator of the solution's distance to the actual mobile devicelocation. This distance can be used with other WLAN AP parameters toweight or select or deselect (remove) an AP in the process ofcalculating the mobile device location.

FIG. 6 shows SPS solution in form of a region 606 and a WLAN positioningsystem 601, in which WLAN access points 604 form a first cluster 602 anda second cluster 603. The mobile device acquisition of two or moresatellites 605 also can result in a set of possible satellite devicesolutions 606. The consistency between the SPS solutions 606 and WLAN-PSsolutions 602 is used to select the best solution, which is the 602solution of WLAN-PS in this example. The consistency between the SPS andWLAN-PS means both of them report the same location as part of theirsolutions or that the final estimated position is one of the solutionsof both systems. Further, a cluster of APs can be weighted according totheir distance to possible solutions of SPS.

Another embodiment of the disclosed subject matter provides a method toweigh WLAN access points by using raw SPS measurements. Selecting thebest set of WLAN access points to estimate end user's location by usingraw SPS measurements can be a specific case of assigning a weight toWLAN APs. In addition to other criteria used to weight or select thebest set of WLAN access points to estimate the mobile device location,raw SPS measurements can be used or combined with the other criteria.Other criteria and weights are weight based on received signal strengthor weight based on round trip time of received signal. The WLAN-PS usesWLAN APs and their characteristics to estimate the location of a mobiledevice.

The characteristics of a WLAN AP might include, but are not limited to,received signal strength (RSS), location or estimation of location,signal to noise ratio, and time of arrival (TOA). Raw SPS measurementsfrom two or more satellites are used to calculate an indication ofdistance between location (or estimated location) of WLAN APs and actuallocation of the mobile device. This indication of distance can be usedto select the best set of WLAN APs to estimate location of the mobiledevice, or the indicator of distance can be used to weight WLAN APsaccording to their distance from the device location. The raw SPSmeasurements from at least two satellites can be used in this process,with or without having a location estimate from SPS. The distance isconsidered far if the distance is more than an order of magnitude largerthan the coverage area of the WLAN AP. A distance is considered close ornot far is the distance is within an order of magnitude of the coveragearea of the WLAN AP. WLAN APs that are considered far can be eliminatedfrom the positioning calculation.

FIG. 7 shows an example of an integrated solution of WLAN-PS and SPS, inwhich the mobile device detects five WLAN access points 702 and hasacquired a signal and raw measurements from two satellites 704. In thisexample, the WLAN access points are randomly spread around the mobiledevice, and distance between WLAN access points 702 and possiblesolutions of two satellites 703 can be used as an indication of distancebetween WLAN access point and actual location of the mobile device. Aregion of possible SPS solutions 703 is calculated using measurementsfrom two satellites. The distance between the WLAN access point 702 andSPS possible solution 703 is used as an indicator of distance betweenWLAN access point and actual location of the mobile device. In thisexample, all the WLAN access points 702-1 are very close to SPS possiblesolutions 703, but one WLAN access point 702-2 is not. Therefore, thelonger distance between WLAN access point 702-2 and possible SPSsolutions 703 is an indicator of a larger distance between WLAN accesspoint 702-2 and the location of the mobile device compared to otherdetected WLAN access points 702-1. Thus, WLAN access point 702-2 can beweighted according to its distance to SPS possible solutions, or it canbe removed from the set of APs to calculate the mobile device location.

FIG. 8 illustrates WLAN-PS 801 and SPS 806 integrated solution, in whichall the modules are the same as FIG. 2, except for selecting WLAN APs803. Selecting WLAN APs 803 also receives raw SPS measurements 311 as aninput. These raw measurements are used to estimate the distance betweenthe location (or estimated location) of WLAN APs and the location of themobile device.

As discussed in the previous embodiment, in this embodiment there is aneed to calculate an indication of the distance between WLAN APslocation (or estimated location) and actual location of the mobiledevice using SPS measurements from two or more satellites. Theconsistency between the raw SPS measurements and the WLAN APs can beused as an indication of distance between the location of WLAN APs andthe location of the mobile device. The consistency can be calculated by(1) using the WLAN AP's location as an estimation of the location of themobile device and (2) calculating the receiver clock bias for each WLANAP location based on the measurements from each satellite. Theconsistency between calculated receiver clock biases can be used as anindicator of distance between WLAN APs location and the mobile device'sactual location.

In other words, after applying the location of a WLAN AP as an initialposition in SPS equations using pseudorange measurements, the onlyremaining unknown is the receiver clock bias, which is the same for allSPS raw measurements. If clock bias which is found for each satellitemeasurement is denoted by Ci, the consistency of Ci is used as a measureof distance between the given position (in this case, location of WLANAP) and the location that satisfies the satellite equations. Consistencyof Ci can be measured with different mathematical approaches, likestandard deviation of Ci, or mean square error of Ci estimation asfollows:

$\overset{\_}{C} = \frac{\sum\limits_{i = 1}^{N}C_{i}}{N}$${M\; S\; E} = \frac{\sum\limits_{i = 1}^{N}\left( {C_{i} - \overset{\_}{C}} \right)^{2}}{N}$

The value of MSE can be used as an indicator of the consistency of theCi samples. Therefore, the location of all the detected WLAN APs can beexamined with SPS raw measurements, and the consistency of Ci can beused as an indicator of their distance to the mobile device location.This indicator can be used with other AP parameters to weight, select,or remove an AP in the process of calculating the mobile devicelocation.

Under another embodiment of the disclosed subject matter, a system andmethod is provided in which the WLAN-PS provides a region in which apossible location solution resides, and within the provided region, thefinal location estimate of the mobile device is selected based on SPSmeasurements from two or more satellites.

FIG. 9 shows an integrated WLAN-PS and SPS, in which WLAN-PS 901provides an estimate of the location of the mobile device with someuncertainty 903. The uncertainty 903 can be the expected error ofWLAN-PS. The mobile device also acquires signal from two or moresatellites 902. Using all the points within the uncertainty area 903reported by WLAN-PS, the location 904 which fits the satellitemeasurements the best is selected as the best estimate of location ofthe mobile device.

The best point which fits satellite solutions within that region can befound by dividing the uncertainty area 903 to small grids and evaluatingeach grid point as is shown in FIG. 10. The distance between grid linescan be based on the required accuracy of location estimation and thequality of the SPS measurements. The higher the accuracy requirement andthe quality of the SPS measurements, the smaller the distance betweenthe grid lines can be and the more accurate the location estimate. Forexample, the grid lines can be between about 5 meters and about 100meters apart, preferably at about 10 meters apart.

In this embodiment, the number of SPS satellites 902 can be two or more.This system or method can be used in cases where the SPS cannotdetermine the location of the mobile device by itself but where theWLAN-PS possible solution 903 can be examined with the SPS informationto select as the best location 904 the one that is most consistent withthe SPS pseudorange equations.

FIG. 11 shows an integrated solution of WLAN-PS 1101 and SPS 1106, inwhich final location estimate provided by WLAN-PS is refined by usingSPS measurements 311 from two or more satellites. A new module, refiningmodule 1111, is added to conventional WLAN-PS, which receives WLAN-PStrilateration results, the corresponding uncertainty of thosemeasurements, and SPS measurements from two or more satellites. Usingthis information, the refining module 1111 reports the location estimateof the mobile device.

For example, if the WLAN-PS provides a sphere of possible locationsolutions to refining module 1111. The size of the sphere corresponds tothe uncertainty of the location estimate of WLAN-PS (expected error),which can be calculated for each position estimate in some embodiments,or the nominal value of uncertainty of WLAN-PS can be used. For example,median error of Skyhook Wireless WLAN-PS is about 30 m, which can beused as nominal value of WLAN-PS error. In the next step, SPSmeasurements from two or more satellites can be used to find a pointwithin the specified region by WLAN-PS, which satisfies the SPSmeasurements the best. The satellite equation for each satellite iswritten as follows:

Fi(x,y,z,b)=0

In which (x, y, z) is location of the mobile device, and b is denotedfor the internal clock bias of SPS receiver. Any point within thespecified region by WLAN-PS provides an estimate for the location of themobile device, (x, y, z), and internal clock bias is calculated for eachacquired satellite. Because all the measurements are done at almost thesame time by the same SPS receiver, the internal clock bias of SPSreceiver should be almost the same for all the SPS measurements.Therefore, as discussed previously, the consistency between receiverclock biases of SPS receiver calculated from different acquiredsatellites can show the distance between location estimate (x,y,z) andactual location of the mobile device. The consistency of the calculatedinternal clock of SPS receiver can be measured by calculating thestandard deviation of the receiver clock bias measurements.

In the case where the specified region by WLAN-PS is divided into agrid, the SPS equations are examined at each grid point. The grid pointwhich provides the most consistent receiver clock bias for all theacquired satellites is the best location estimate of the mobile device.

Another embodiment of the invention provides a method to reduceacquisition time of SPS by providing a position estimate of WLAN-PS asan initial position to SPS. Providing an initial position by WLAN-PS canreduce the acquisition period of the SPS and therefore reduces time tofirst fix of SPS. Satellite positioning systems already provide a methodto receive an initial position, and how they use the provided initialposition inside SPS is generally known. The present system uses aWLAN-PS location estimate as a source of initial position for thesatellite positioning system. Because the location of SPS satellites areknown at any time, knowledge of a rough location of the mobile devicecan help the SPS to reduce the set of satellites it searches for to theset of satellites actually visible to the device, instead of all of thesatellites, thereby reducing searching time.

FIG. 12 illustrates a WLAN-PS 201 and SPS 1203, in which WLAN-PSprovides an initial position 1211 to the SPS system. Thus, the estimatedlocation of the mobile device 1211 by the WLAN-PS 201 can be provided asinitial position to SPS 1202. Knowing the initial position of the mobiledevice can assist SPS 1202 to select the best set of the satellites tosearch and reduce time to fix a location of the device.

The WLAN-PS and the SPS can work independently and provide estimates ofattributes of a mobile device, including location estimation, expectederror in the location estimation, velocity, and bearing estimation.However, because WLAN-PS has a much shorter time to first fix (TTFF)than SPS, the estimated location by WLAN-PS can be provided to SPS asinitial position of the mobile device, reducing the time required tofind location.

The receipt of an initial position is a standard practice in SPS, andmost of the SPS receivers provide a method to receive the initialposition. Here the WLAN-PS is used as the source of providing theinitial position to SPS.

Another embodiment of the invention provides a method to increase theaccuracy of the expected error of location estimate of the integratedlocation solution of SPS and WLAN-PS and compare the error to the errorlocation result for each individual system. The expected errorestimation provides an uncertainty area around the estimated location.If estimated location of WLAN-PS and SPS are within the uncertainty areaof each other, the uncertainty area is reduced based on distance betweenestimated locations from both systems. If estimated locations of WLAN-PSand SPS are not within the uncertainty area of each other, theuncertainty area is increased based on distance between estimatedlocations from both systems. If only one of the estimated locations ofWLAN-PS and SPS falls inside the uncertainty area of the other system,the uncertainty area can be reduced or increased based on quality ofestimated error from each system. The estimated error of locationestimate normally reports the 95% confidence interval, but it can reportany other confidence interval as well.

Another embodiment of the invention provides a method to increase theaccuracy of the expected error of a location estimate of the integratedlocation solution of SPS and WLAN-PS. The WLAN-PS provides a locationestimate and the SPS acquires at least two satellites. The expectederror estimation provides an uncertainty area around the estimatedWLAN-PS location. The consistency between the estimated location ofWLAN-PS and raw SPS measurements is used as criteria to reduce orincrease the expected error estimate. If estimated location estimate ofWLAN-PS and raw SPS measurements are consistent, the uncertainty area isreduced based on distance between WLAN-PS estimated location from SPSpossible solutions. If the estimated location of WLAN-PS and raw SPSmeasurements are not consistent, the uncertainty area is increased basedon distance between WLAN-PS estimated locations from SPS possiblesolutions.

FIG. 13 illustrates WLAN-PS location estimation 1301 and WLAN-PSexpected error of estimation 1303 and also SPS location estimation 1302and SPS expected error of estimation 1304. The reported uncertainty byeach system is the expected error of position estimate.

In such a system, the SPS and WLAN-PS each provides a location estimateand also an estimate of the expected error in that location estimation.The expected errors of the location estimate provided by both systemsare combined in order to provide a better estimate of the error of thelocation estimation. For example, if each system provides an area aroundthe reported location as an uncertainty of the estimated location (1303and 1304), the integrated system considers the overlap of theuncertainty areas 1305 and also the distance between estimated locations1306 to estimate the uncertainty of the final location estimate. Thegreater the distance between the estimated locations by SPS and WLAN-PSis, the higher the expected error of location estimation. In anotherimplementation, the system can select the location estimate with thelowest uncertainty as the final location estimate.

FIG. 14 illustrates a block diagram of integrated WLAN-PS and SPSsystem, in which the expected error of each system is calculated usingconventional method and the results are provided to integrated errorestimation system device 1411. The integrated error estimation 1411calculates the final expected error by considering the consistencybetween the reported locations by WLAN-PS and SPS. The consistency canalso be determined by comparing the receiver clock bias, as discussedpreviously.

In some embodiments, the SPS can detect that the mobile device isstationary. In general, it takes measurements from four SPS satellitesto estimate the velocity or speed of a mobile device. The present methodand system can determine if the mobile device is stationary by using themeasurements from as few as two satellites by examining the consistencyof the Doppler frequency measurements from the two or more satellites.If the device is stationary, the Doppler measurements from SPS must befully accounted for by satellite motion relative to initial position ofthe device and the frequency offset of the receiver clock. The receiverclock offset can be estimated, given the Doppler measurements from twoor more satellites. The hypothesis that the user is stationary is basedon the size of the residuals after the estimated receiver frequency biasis substituted in the SPS Doppler equations.

By knowing that a mobile device is stationary, the hybrid system cancause the WLAN-PS to respond differently than when the device is inmotion. For example, WLAN-PS can save power by updating the locationless often, for example, once a minute. In addition, the WLAN-PS canconsider all of the detected WLAN access points over the time intervalthat the mobile device is stationary and use the collective informationto estimate an improved location of the mobile device. This is becausethe WLAN-PS can obtain a better estimate of the received signal strengthfrom an access point and better mitigate power fluctuation due tomulti-path when user is stationary. Multipath is the propagationphenomenon that results in radio signals reaching the receiving antennaby two or more paths and causes power to fluctuate, and it is a knownphenomena by experts in the radio propagation field.

FIG. 15 illustrates stationary user detection based on two or moresatellites.

If the mobile device 1503 detects two or more satellites, 1501, 1502 onecan determine that the mobile device is stationary or moving fromDoppler measurement of the received signal from satellites.

The first step is finding a rough location of the mobile device 1503,which can be calculated by WLAN-PS. This rough estimate of location ofthe mobile device can be provided by other positioning technologies aswell. The rough estimation of the location of the mobile device can havean error of up to about a couple of kilometers although accuracy ofrough estimation of location by WLAN-PS is maximum couple of hundredmeters.

The mobile device can acquire a signal from at least two satellites,which are shown with satellites 1501 and 1502 in FIG. 15. The mobiledevice also knows the velocity of the satellites at the exact time ofsignal acquisition. In other words, if the mobile device 1503 acquires asignal from satellites 1501 and 1502 at time t, the velocity of thesatellites at time t also is known by the mobile device. The mobiledevice 1503 can determine the velocity of the acquired satellites 1501and 1502 by decoding the messages received from the satellites, as allsatellite broadcasts its velocity at any moment of time. The mobiledevice can also receive satellite velocity from other sources, forexample, a cellular network.

Velocity is a vector with magnitude and direction, and it was shown withvelocity of V₁ and V₂ for satellites 1501 and 1502, respectively.Doppler frequency due to satellite movement is calculated based onvelocity. The simplified equation to find Doppler frequency for eachsatellite is as follows:

$\begin{matrix}{{f_{d\; 1} = \frac{v_{1}}{\lambda}}{f_{d\; 2} = \frac{v_{2}}{\lambda}}} & (1)\end{matrix}$

The λ is wavelength of SPS radio wave and it is known for any SPSsystem, and f_(d) is the Doppler frequency.

The mobile device measures the frequency of the received signal fromeach satellite. Since the transmit frequency of each satellite is known,the mobile device can measure the difference between the frequency ofthe received signal and the transmitted signal. The difference betweenreceived and transmitted frequency are denoted by f_(o) and f₁₂ forsatellites 1501 and 1502, respectively.

If the mobile device frequency offset of the internal clock is f_(o) andthe velocity of the mobile device 1503 is ν_(m), the measured frequencyfrom each satellite is calculated as follows:

$\begin{matrix}{{{{f_{d\; 1}{\cos \left( \alpha_{1} \right)}} + f_{o} + {\frac{v_{m}}{\lambda}{\cos \left( \beta_{1} \right)}}} = f_{m\; 1}}{{{f_{d\; 2}{\cos \left( \alpha_{2} \right)}} + f_{o} + {\frac{v_{m}}{\lambda}{\cos \left( \beta_{2} \right)}}} = f_{m\; 2}}} & (2)\end{matrix}$

The angles α_(l) and α₂ are between the velocity vector of thesatellites and the lines connecting the mobile device to the satellitesfor satellite 1501 and 1502, respectively. The mobile device cancalculate the angles based on the devices location, the location of thesatellites, and the velocity vector of the satellites. If the mobiledevice is stationary, the above equations are rewritten as follows:

f _(d1) cos(α₁)+f _(o) =f _(m1)

f _(d2) cos(α₂)+f _(o) =f _(m2)  (3)

The only unknown for the mobile device in these equations is f_(o), andit can be found from each satellite equation independently. If themobile device is stationary, the values of f₀ from all the acquiredsatellites are going to be the same. In other words, if the values of f₀from equations for all the acquired satellites are not the same, themobile device is not stationary.

Another embodiment of the disclosed subject matter relates to a methodfor providing characteristics of the environment of a mobile device byusing WLAN-PS. WLAN APs are stationary radio transceivers withrelatively small coverage, which are surveyed for positioning purposes.During the survey process, one of the characteristics associated withthe WLAN APs can be characteristics of the environment. Then thedetected WLAN access points by a mobile device are used collectively todetermine the environment in which a mobile device is operating. Theenvironmental characteristics can be considered as attributes of WLANaccess points, for example, density of buildings near the AP height ofbuildings near AP, and whether the AP is in an urban canyon, urban, orsuburban location. The data on the environmental characteristics of theaccess points can reside in the reference database of the access pointsand can be obtained there by the user device. The granularity of thearea, which is characterized by WLAN access points, can be different,and it can be as small as a building or as big as a neighborhood.Environmental information can be used by SPS, WLAN-PS, and also anintegrated solution of both systems to adjust the systems approach toposition acquisition and/or for power management. For example, knowledgeof the fact that a mobile device is in an urban canyon environment mightcause the hybrid system to rely on WLAN-PS alone, while in a suburbanenvironment, SPS might be considered as the primary source of estimationof position and other attributes of the mobile device.

Another embodiment of the disclosed subject matter and system provides amethod to maintain the stability of the internal clock of a SPS receiverby using the WLAN APs. This can be accomplished by measuring known timeintervals of the signal transmitted by a WLAN device equipped with astable clock. Maintaining the internal clock stability of a SPS receiveris important for position determination. For example, it can help inacquiring satellite signals faster, being able to operate at lowerpower, and also providing a fix (location estimation) with fewersatellites. A WLAN standard defines constant time intervals, including,but not limited to, some packet headers, some fields in some packets, asin WLAN 802.11 standard DIFS (DCF Inter Frame Space), SIFS (Short InterFrame Space), or slot duration, and a mobile device can use these knowntime intervals to measure its internal clock bias over time and maintainits stability.

There might be WLAN access points with different clock stability. Inthis case, data identifying the access points which are equipped with astable clock can be considered as part of characteristics of the WLAN APand/or the characteristics can reside in the access point data base andcan be obtained from there.

In addition to providing initial position and clock information, theWLAN positioning system can provide clock updates to the WLAN-enabledSPS receiver. Every SPS receiver is equipped with an internal oscillatorin order to maintain its indication of GPS clock information. However,because these oscillators are imperfect at maintaining an exactmeasurement of time, the clocks internal to the SPS receivers drift.This clock drift can cause position estimation errors. By the WLAN-PSproviding the correct GPS clock information to the SPS system, the WLANpositioning system facilitates avoiding such position estimation errors.Furthermore, because the SPS receivers are able to maintain a highlyaccurate measure of the GPS clock information, they can operate atrelatively lower signal to noise ratio (SNR) values in the positionestimation calculations. Maintaining SPS timing by SPS receiver reducestime uncertainty of received signals from satellites. Therefore, it iseasier to extract signal from noise, and SPS receiver can detect weakersignal and operate in harsher locations in terms of SPS signal. Thusaspects of the method allow SPS receivers to operate in areas havingless that ideal SPS signal conditions.

Another embodiment of the present disclosure relates to using WLANmunicipal networks to increase the accuracy of SPS receiver estimationsby providing initial timing and location information to the SPSreceiver. WLAN municipal networks are city wide WLAN networks which areinstalled in city by city officials or under their supervision toprovide wireless connection using WLAN technology. Aspects of thismethod and system of improving SPS receiver position estimation accuracyby using WLAN municipal network data consists of the following items:

In order to assist the SPS position estimation by providing GPS clockinformation, the municipal WLAN access points should be synchronizedwith the GPS clock. WLAN access points of a municipal network can besynchronized with the GPS clock by using one of the following methods asexamples: (1) use of SPS enabled WLAN APs where each WLAN AP in amunicipal network can be equipped with a device which extracts the GPSclock information from GPS radio signals, (2) use of centralized clockdistribution entity synchronized where the GPS clock information can beextracted at one place and then distributed to all the WLAN APs in themunicipal network, and (3) use of a high quality oscillator in WLAN AP.An oscillator is used to measure time and maintain synchronization withthe GPS clock. As long as the quality of the WLAN AP oscillator ishigher than the SPS receiver oscillator, the timing provided by the WLANAP is going to be higher than the SPS receiver. Therefore, the SPSreceiver can use WLAN AP to maintain its timing better than using itsinternal clock. The single module that extracts the GPS clockinformation (herein “Clock Distribution Entity”) is the only unit andonly place which extracts the GPS clock information and then providestiming to all the WLAN access points in the network.

Further, when the WLAN receiver is integrated into the SPS receiver theSPS receiver can use the WLAN receiver to extract timing informationfrom the signals received from WLAN access points of WLAN municipalnetworks. While the idea of providing initial timing to SPS receiver hasbeen explained for WLAN municipal networks, it can be applied to anyWLAN network which is synchronized to a GPS clock.

Upon review of the description and embodiments of the present invention,those skilled in the art will understand that modifications andequivalent substitutions may be performed in carrying out the inventionwithout department from the essence of the invention. Thus the inventionis not meant to be limiting by the embodiments described explicitlyabove and is limited only by the claims which follow. Further, thefeatures of the disclosed embodiments can be combined, rearranged, etc.,within the scope of the invention to produce additional embodiments.

1. A method of determining the location of a WLAN and satellite enableddevice by using satellite measurements and satellite information toweigh WLAN access points (APs), the method comprising: identifying WLANAPs in range of the WLAN and satellite enabled device; retrievinglocation estimates of the WLAN APs; grouping the WLAN APs into clustersof at least one WLAN AP based on the location estimates of the WLAN APs;obtaining satellite measurements and satellite information from at leasttwo satellites to provide a plurality of possible satellite-basedlocations of the device; and providing a weight for each cluster of WLANAPs based on a distance from the clusters of WLAN APs to the nearestlocation among the plurality of possible satellite-based locations ofthe device.
 2. The method of claim 1 comprising using the weight foreach cluster of WLAN APs in a location algorithm to determine thelocation of the device.
 3. The method of claim 1, wherein the pluralityof possible satellite-based locations of the device comprise a region ofpossible location solutions for the device.
 4. The method of claim 1,wherein a relatively higher weight corresponds to a cluster of WLAN APswhose location estimate is closer to the plurality of possiblesatellite-based locations of the device relative to the locationestimates of the other clusters of WLAN APs.
 5. The method of claim 4,wherein a location estimate of a cluster of WLAN APs is closer to theplurality of possible satellite-based locations of the device if thelocation estimate of the cluster of WLAN APs comprises a distance withinabout one order of magnitude of the coverage area of the cluster of WLANAPs.
 6. The method of claim 1, wherein a relatively lower weightcorresponds to a cluster of WLAN APs whose location estimate is fartherfrom the satellite-based estimation of the location of the devicerelative to the location estimates of the other clusters of WLAN APs. 7.The method of claim 6, wherein a cluster of WLAN APs is farther from thesatellite-based estimation of the location of the device if the locationestimate of the cluster of WLAN APs comprises a distance about an orderof magnitude above the coverage area of the cluster of WLAN APs.
 8. Themethod of claim 6, wherein if the location estimate of the cluster ofWLAN APs is determined to be farther from the plurality of possiblesatellite-based locations of the device, the position of the WLAN andsatellite enabled device is calculated without data from the far clusterof WLAN APs.
 9. The method of claim 1, wherein the weights are based onthe consistency between the location estimates of the clusters of WLANAPs and the plurality of possible satellite-based locations of thedevice.
 10. The method of claim 1, wherein the location estimates of theclusters of WLAN APs are based on characteristics of the WLAN APs of theclusters, the characteristics including at least one of received signalstrength, location of the WLAN APs, signal-to-noise ratio, time ofarrival, and last-known location of the WLAN APs.
 11. The method ofclaim 1, wherein the plurality of possible satellite-based locations ofthe device is based on a subset of the satellite measurements andsatellite information.
 12. The method of claim 1, wherein the satellitemeasurements and satellite information is obtained from less than foursatellites.
 13. The method of claim 1 comprising: eliminating, from usein determining the location of the WLAN and satellite enabled device,clusters of WLAN APs whose location estimates are not consistent withthe plurality of possible satellite-based locations of the device. 14.The method of claim 13, wherein the WLAN AP cluster location consistencywith the satellite measurements and satellite information is measured byapplying each of the WLAN AP cluster location estimates to the satellitemeasurements and satellite information, and calculating the internal SPSreceiver clock bias for each WLAN AP cluster location estimate.
 15. Themethod of claim 13, comprising calculating an internal SPS receiverclock bias by considering (i) the location estimates of each cluster ofWLAN APs as an initial position and (ii) the measurements andinformation from each satellite.
 16. The method of claim 13, wherein theconsistency of the internal SPS receiver clock bias for each of the WLANAP cluster location estimates is used as an indication of distancebetween the WLAN AP cluster location estimate and the plurality ofpossible satellite-based device locations.
 17. The method of claim 13,wherein calculating the consistency of the internal SPS receiver clockbias for each WLAN AP cluster location estimate comprises calculatingthe standard deviation or the mean square error of the internal SPSreceiver clock bias.
 18. A system for determining the location of a WLANand satellite enabled device by using satellite measurements andsatellite information to weigh WLAN access points (APs), the systemcomprising: a hybrid positioning module comprising: a WLAN positioningmodule for receiving information from one or more WLAN APs, forreceiving location estimates of the one or more WLAN APs, and forgrouping the WLAN APs into clusters of one or more WLAN APs based on thelocation estimates of the one or more WLAN APs; a satellite positioningmodule for providing a plurality of possible locations of the WLAN andsatellite enabled device based on satellite measurements and satelliteinformation from at least two different satellites; and logic containedin the hybrid positioning module for providing a weight for each clusterof WLAN APs based on the distance from the clusters of WLAN APs to thenearest location estimate among the plurality of possiblesatellite-based locations of the device.
 19. The system of claim 18,wherein a relatively higher weight corresponds to a cluster of WLAN APswhose location estimate is closer to the plurality of possiblesatellite-based locations of the device relative to the other clustersof WLAN APs.
 20. The system of claim 19, wherein a cluster of WLAN APsis closer to the plurality of possible satellite-based locations of thedevice if the location estimate of the cluster of WLAN APs comprises adistance within about one order of magnitude of the coverage area of thecluster of WLAN APs.
 21. The system of claim 18, wherein a relativelylower weight corresponds to a cluster of WLAN APs whose locationestimate is farther from the satellite-based estimation of the locationof the device relative to the other clusters of WLAN APs.
 22. The systemof claim 21, wherein a cluster of WLAN APs is farther from thesatellite-based estimation of the location of the device if the locationestimate of the cluster of WLAN APs is at a distance about an order ofmagnitude above the coverage area of the cluster of WLAN APs.
 23. Thesystem of claim 22, wherein if the location estimate of the cluster ofWLAN APs is determined to be farther from the plurality of possiblesatellite-based locations of the device, the position of the WLAN andsatellite enabled device is calculated without data from the farthercluster of WLAN APs.
 24. The system of claim 18, wherein the weights arebased on the consistency between the location estimates of the clustersof WLAN APs and the plurality of possible satellite-based locations ofthe device.
 25. The system of claim 18, wherein clusters of WLAN APswhose location estimates are not consistent with the plurality ofpossible satellite-based locations of the device are eliminated from usein determining the location of the WLAN and satellite enabled device.26. The system of claim 24, wherein the WLAN AP cluster locationconsistency with the satellite measurements and satellite information ismeasured by applying each of the WLAN AP cluster location estimates tothe satellite measurements and satellite information, and by calculatingthe internal SPS receiver clock bias for each WLAN AP cluster locationestimate.
 27. The system of claim 24 comprising calculating an internalSPS receiver clock bias by considering (i) the location estimate of eachcluster of WLAN APs as an initial position and (ii) the measurements andinformation from each satellite.
 28. The system of claim 24, wherein theconsistency of the internal SPS receiver clock bias for each of the WLANAP cluster location estimates is used as an indication of distancebetween the WLAN AP cluster location estimate and the plurality ofpossible satellite-based locations.
 29. The system of claim 24, whereincalculating the consistency of the internal SPS receiver clock bias foreach WLAN AP cluster location estimate comprises calculating thestandard deviation or the mean square error of the internal SPS receiverclock bias.
 30. The system of claim 18, wherein the location estimatesof the clusters of WLAN APs are based on characteristics of the WLAN APsof the clusters, the characteristics including at least one of receivedsignal strength, location of the WLAN AP, signal-to-noise ratio, time ofarrival, and last-known location of the WLAN AP.
 31. The system of claim18, wherein the plurality of possible satellite-based locations of thedevice is based on a subset of the satellite measurements and satelliteinformation.
 32. The system of claim 18, wherein the satellitemeasurements and satellite information is obtained from less than foursatellites.